Recently, as communication techniques are advanced and use of the Internet is expanded, searches are performed in various ways. For example, a computer user may acquire desired information through Internet searches (further specifically, web services), in addition to directly consulting a dictionary or asking a person familiar with the related information, in order to locate the information that the computer user desires to know. That is, after connecting to a web server which provides a search service using a web browser, the computer user may input keywords related to the desired information and receive the search service associated with the web server.
The search service is developed into a variety of types. Particularly in Korea, utilization of search for acquisition of information tends to increase and importance of knowledge search increases. The search service is a function used by a large number of users. In addition, it is general that visits of users to a web site is directly related to advertisement revenues. Thus, a large number of portal sites actually provide search functions.
However, although the number of the sites providing the search functions increases, most of the search functions are generally based on a text search, such as a keyword search or the like. Thus, they do not satisfy desires of users who want to easily obtain desired information in diverse ways.
Particularly, if the desired information is formed of an image, instead of text, in a conventional method, a keyword that is supposed to be related to the corresponding image is first inferred and then, the search is performed by inputting the relevant keyword. Although it is possible to show only the corresponding image results by setting a search range, the image search itself is merely a kind of text-based (keyword-based) search.
This method has a problem that if a user does not know what a corresponding image relates to, it is difficult to infer a relevant keyword, and accordingly, the number of inputting keywords for the search is increased and the desired information may not be easily searched for.
Accordingly, in order to solve the problem, an image search system has been developed, in which, when a user desires to obtain information on a specific image, a search using the image itself, instead of the text-based search, may be performed.
However, the image search system also has problems as described below. First, in order to provide such an image search system, an image database containing a sufficient amount of data is required. When a sufficient amount of data is not contained in the image database, even if a query image is input, it may be possible to fail to provide search result information for the query image. In addition, all of the images which caused a failed result in matches of the query images and the images stored in the image database, i.e., unrecognized images, are discarded, instead of being reused. In this case, until the unrecognized images are manually reflected into the image database, despite repeated searches, it is impossible to provide a search result for the unrecognized images.
As one of techniques for solving the problems, Korean Patent No. 10-1029160 is disclosed by the applicant of the present application. In this technique, if the matching between an input query image and images stored in the image database end in failure, the query image is stored in an unrecognized image database. In the unrecognized image database, the images having an association relationship are collected into image groups based on similarities therebetween. Then, when a specific image and tag information thereon are input from the outside, at least some images of a specific image group in the unrecognized image database are compared with the specific input image to determine whether a similarity therebetween is equal to or higher than a predetermined threshold value. If it is determined that the similarity therebetween is equal to or higher than the predetermined threshold value, at least some images in the unrecognized image database are automatically added, together with the input tag information, to the recognized image database.
However, this technique is disadvantageous in that its configuration is complicated since the unrecognized image database is separately required in addition to the image database. In addition, there is a problem in that the unrecognized images of the image groups stored in the unrecognized image database cannot be used in image recognition and cannot be provided as a search result until a query image (a query image containing tag information) having a similarity with them being equal to or higher than a threshold value is input.